1. Field of the Invention
The invention relates in general to the measurement of digital signals and, in particular, to a method and system for determining characteristics of a digital signal utilizing an eye diagram generated from the measured characteristics of the digital signal.
2. Related Art
An eye diagram is an important analysis tool in the study of serial data communication systems. Specifically, an eye diagram analysis is an important tool for studying the behavior of high-speed digital electrical and optical communications signals.
An eye diagram is formed by overlapping signal waveforms of a digital data signal over a specified time interval. Generally, the eye diagram is a composite image of the waveform shapes of logic one-zero combinations of the digital data signal, where the composite image is typically displayed on an oscilloscope or other suitable display device. Eye diagrams of high speed digital signals are often generated using either an equivalent-time sampling oscilloscope (such as, for example, an 86100B sampling oscilloscope produced by Agilent Technologies of Santa Clara, Calif.) or a real-time oscilloscope (such as, for example, an Infiniium 90000 X-Series oscilloscope produced by Agilent Technologies). In general, an eye diagram is a conventional format for representing parametric information about a digital signal and provides a qualitative means to evaluate link performance and to troubleshoot system issues.
By measuring and analyzing features of the generated eye diagram, various characteristics of a digital data signal, such as signal-to-noise ratio, extinction ratio, jitter, duty cycle distortion, and the like, and its channel impairments such as inter-symbol interference (“ISI”) can be readily determined.
In general, a real-time oscilloscope, sometimes called a “single-shot” scope, captures an entire waveform of an input signal on each trigger event. On the other hand, an equivalent time sampling oscilloscope, sometimes simply called a “sampling scope,” measures only the instantaneous amplitude of the waveform at the sampling instant. In contrast to the real-time oscilloscope, the input signal is only sampled once per trigger. As such, an advantage of a real-time oscilloscope is that it is able to display one-time transient events, measures cycle to cycle jitter directly, and does not require an explicit trigger or a repetitive waveform. A disadvantage is that it generally requires large record lengths and deep memory.
Stating that a real-time oscilloscope captures an entire waveform on each trigger event means that a large number of data points are captured in one continuous record. To better understand this type of data acquisition, a real-time oscilloscope may be thought as being an extremely fast analog-to-digital converter (“ADC”) in which the sample rate determines the sample spacing and the memory depth determines the number of points that will be displayed. In order to capture any waveform, the ADC sampling rate needs to be significantly faster than the frequency of the incoming waveform such as at least twice the Nyquist sampling rate. This sample rate, which presently can be as fast as 80 Giga-samples per second (“GSa/s”), determines the bandwidth which currently extends to about 32 GHz.
In FIG. 1, a plot 100 of an example of an input signal 102 is shown. In this example, the input signal 102 is sampled by a real-time oscilloscope. The real-time oscilloscope may be triggered on a feature of the input signal 102 itself, as an example, the trigger signal 104 may occur when the amplitude of the waveform of the input signal 102 reaches a certain threshold 106. At that point, the real-time oscilloscope starts converting the analog waveform of the input signal 102 to digital data sample points 108 at a rate asynchronous and unrelated to the data rate of the input signal 102. The sampled points 108 may then be used to create a digital reconstructed data signal 110 that is the digitized version of the input signal 102. That conversion rate, known as the sampling rate, is typically derived from either an internal clock signal of the real-time oscilloscope or an external provided clock, herein generally referred to a “ADC clock signal 112.” In general, the real-time oscilloscope preforms a process that includes sampling the amplitude of the waveform of the input signal 102, storing that value in memory, and continuing to the next sample until the a predefined length of the input signal 102 has been captured by the real-time oscilloscope. The main job of the trigger signal 104 is to provide a horizontal time reference point 114 for the incoming data of the input signal 102 relative to a period 116 of the clock signal 112.
In FIGS. 2A through 2D, four plots 200, 202, 204, and 206 of voltage 208 versus time 210 for four example digital signals 212, 214, 216, and 218 are shown that are three time periods long and vary in amplitude between a low Voltage VL and high voltage VH. In these examples, FIGS. 2A through 2D show four patterns that illustrate the transitions that can occur during the time interval. For example, digital signals 212, 214, 216, and 218 may represent, for example, 001, 011, 100, and 110, respectively. In this example, when the digital signal voltage amplitude is at or below the VL, it is assigned a “0” value. Alternatively, when the digital signal voltage amplitude is at or above the VH, it is assigned a “1” value. In this example, the rising edge transitions 220 and 222 are shown when the digital signal changes from a “0” value to a “1” value. Similarly, in this example, the failing edge transitions 224 and 226 are shown when the digital signal changes from a “1” value to a “0” value. When the four patterns of FIGS. 2A through 2D are superimposed on each other the resulting pattern plot 228 of voltage 230 versus time 232 shown in FIG. 2E is known as an eye diagram.
In FIG. 3, a plot 300 of an eye diagram of voltage 302 versus time 304 is shown. The eye diagram plot 300 may assist in determining noise, jitter, distortion, and signal strength among many other measurements. It gives an overall statistical view of the system under test's performance as it looks at an overlay of every combination of bits in the bit steam of a digitized received input signal 102. As such, by looking at plot 300 of the eye diagram a number of signal characteristics of the input signal 102 may be derived. As an example, a zero level 306, one-level 308, eye amplitude 310, rise time 312, fall time 314, eye height 316, eye width 318, jitter 320, and bit rate 322 may be readily approximated by visual inspection of the plot 300 of the eye diagram.
In this example, the zero level 306 is a measure of the mean value of the logical “0” of an eye diagram plot 300 and the one level 308 is a measure of the mean value of the logical “1” of an eye diagram plot 300. The eye amplitude 310 is the difference between the logic 1 level and the logic 0 level histogram mean values of an eye diagram plot 300. The rise time 312 is a measure of the transition time of the data from a 10% level to a 90% level on the upward slope of the eye diagram plot 300 and the fall time 314 is a measure of the transition time of the data from a 90% level to a 10% level on the downward slope of an eye diagram plot 300. The eye height 316 is a measure of the vertical opening of an eye diagram plot 300 where an ideal eye opening would be measured from the one level 308 to the zero level 306. However, as noise on the input signal 102 increases, the effect will be to cause the eye diagram to “close.” As such, the eye height 316 measurement determines the eye diagram closure due to noise on the input signal 102. Similarly, the eye width 318 is a measure of the horizontal opening of an eye diagram plot 300. Ideally, the eye width 318 would be measured between the crossing points 324 and 326 of the eye diagram plot 300. However, jitter may appear on the input signal 102 and influence the eye opening where jitter is a measure of signal quality and is defined as the measure of variance in signal characteristics such as the variation in time of the signal to its ideal location. One form of jitter that is readily visible on the eye diagram plot 300 is deterministic jitter 320 which is the deviation of a transition from its ideal time caused by reflections relative to other transitions. Finally, the bit rate 322 (also known as the data rate) is the inverse of bit period where the bit period is a measure of the horizontal opening of an eye diagram plot 322 at the crossing points 324 and 326 of the eye diagram. The bit rate 322 may also be referred to as a symbol cell or unit interval (“UI”) width of the eye diagram opening 318 which corresponds to one bit period of the input signal 102.
Turning to FIG. 4A, a plot 400 of voltage 402 versus time 404 is shown of an example acquired waveform of an input signal 406 received by a real-time oscilloscope. The real-time oscilloscope may utilize a precise clock (such as the ADC clock signal 112 shown in FIG. 1) to sample the input signal 406 into a plurality of waveform segments 408 (each having a UI width), shown in FIG. 4B, which may be overlaid 410 on top of each other, as shown in FIG. 4C, so as to create one plot of the eye diagram plot 300 (as shown in FIG. 3).
Due to random jitter and noise as well as deterministic jitter caused by various pattern lengths in the data a real-time oscilloscope an acquired input signal 102 (or 406) may require millions of bits to fully appreciate the input signal 102 (or 406). As an example, a real-time oscilloscope having a sampling rate of 40 GSa/s would produce 40 million sample points 108 for a 1 millisecond (“ms”) capture of the input signal 102. If, as an example, the input signal 102 was a digital signal having 400,000 bits of information that repeats every 1 ms, the reconstructed data signal 110 would have 40 million sample points 108 and every bit in the input signal 102 would have 100 sample points or 100 to 1 oversampling of data relative to the ADC clock of the input signal 102. As another example, a real-time oscilloscope having a sampling rate of 80 GSa/s would produce 160 million sample points of raw data for a 2 ms input signal 102.
As such, to fully construct an eye diagram that begins to accurately represent an input signal 102, a very large amount of data needs to be processed because the signal acquisition of the digital signal 102 may contain millions of bits of data and every bit may contain a large number of sample points. This may result in hundreds of millions of data points that need to be displayed on the oscilloscope display screen in order to construct the entire eye diagram. This may take a long time because the oscilloscope needs to calculate both voltage and time coordinates for every point that is going to be displayed on the display screen. Such a length of time can negatively affect the efficiency and profitability of real-time oscilloscope and others that use the real-time oscilloscope to perform eye diagram analysis. Additionally, most users care more about how an eye diagram closes into its center than they do about the generation of a fully detailed eye diagram from the digital data.
As such, there is a need for an improved real-time oscilloscope that utilizes an improved technique for generating a real-time eye diagram that provides for a reduction in test time.